We present a new method of finding protoclusters using tomographic maps of Ly \alpha Forest flux .
We review our method of creating tomographic flux maps and discuss our new high performance implementation , which makes large reconstructions computationally feasible .
Using a large N -body simulation , we illustrate how protoclusters create large-scale flux decrements , roughly 10 h ^ { -1 } Mpc across , and how we can use this signal to find them in flux maps .
We test the performance of our protocluster finding method by running it on the ideal , noiseless map and tomographic reconstructions from mock surveys , and comparing to the halo catalog .
Using the noiseless map , we find protocluster candidates with about 90 % purity , and recover about 75 % of the protoclusters that form massive clusters ( > 3 \times 10 ^ { 14 } h ^ { -1 } M _ { \odot } ) .
We construct mock surveys similar to the ongoing COSMOS Lyman-Alpha Mapping And Tomography Observations ( CLAMATO ) survey .
While the existing data has an average sightline separation of 2.3 h ^ { -1 } Mpc , we test separations of 2 – 6 h ^ { -1 } Mpc to see what can be tolerated for our application .
Using reconstructed maps from small separation mock surveys , the protocluster candidate purity and completeness are very close to what was found in the noiseless case .
As the sightline separation increases , the purity and completeness decrease , although they remain much higher than we initially expected .
We extended our test cases to mock surveys with an average separation of 15 h ^ { -1 } Mpc , meant to reproduce high source density areas of the BOSS survey .
We find that even with such a large sightline separation , the method can still be used to find some of the largest protoclusters .